New technique to test for prostate cancer

9 September 2014

A team of researchers at Guangdong Medical College in China has
demonstrated the potential of a new test to detect prostate cancer
combining
surface-enhanced Raman scattering (SERS) with a new technique called
support vector machine (SVM).

As described in the journal Applied Physics Letters they
combined SERS and SVM and applied them to blood samples collected
from 68 healthy volunteers and 93 people who were clinically
confirmed to have prostate cancer. They found their technique could
identify the cases of cancer with an accuracy of 98.1%.

If the technique proves safe and effective in clinical trials, it
may become a new method to improve the early detection and diagnosis
of this type of cancer, said Li.

“The results demonstrate that label-free serum SERS analysis
combined with SVM diagnostic algorithm has great potential for
non-invasive prostate cancer screening,” said Li. “Compared to
traditional screening methods, this method has the advantages of
being non-invasive, highly sensitive and very simple for prostate
cancer screening.”

Need for a new method of diagnosis

While a simple blood test for elevated levels of a protein marker
known as prostate specific antigen (PSA) has been used for years to
screen for early cases of prostate cancer, the test is far from
perfect because the elevated PSA levels can be caused by many things
unrelated to cancer. This contributes to over-diagnosis,
uncomfortable tissue biopsies and other unnecessary treatment, which
can be costly and carry significant side effects.

According to Li, many scientists have thought about applying SERS
to cancer detection because the surface-sensitive type of
spectroscopy has been around for years and is sensitive enough to
identify key molecules in very low abundance, like pesticide
residues on a contaminated surface. This would seem to make it
perfect for spotting subtle signals of DNA, proteins or fatty
molecules that would mark a case of cancer.

The challenge, he said, was that these changes were, if anything,
too subtle. The signal differences between the serum samples taken
from the 68 healthy volunteers and the 93 people with prostate
cancer were too tiny to detect. So to accurately distinguish between
these samples, Li’s group employed a powerful spectral data
processing algorithm, support vector machine (SVM), which
effectively showed the difference.

While the work is preliminary, it shows that serum SERS
spectroscopy combined with SVM diagnostic algorithm has the
potential to be a new method for non-invasive prostate cancer
screening, Li said. The next research step, he added, is to refine
the method and explore whether this method can distinguish cancer
staging.